Risk management on Thetabruv

Risk measures

Mon, 01 Jan 0001 00:00:00 +0000

Risk measures#

There’s an uncomfortable fact at the center of this page: the world’s most widely used risk metrics — volatility, Sharpe ratio, Information Ratio — are systematically generous to volatility selling strategies. Not slightly generous: spectacularly so. A well-built short vol strategy posts numbers no traditional manager can dream of, and those numbers are simultaneously true and misleading. Understanding why is the prerequisite for not falling in love with your own track record. I’ll proceed in layers: first the dispersion metrics, then the tail metrics, finally the operational ones.

Tail risk

Mon, 01 Jan 0001 00:00:00 +0000

Tail risk#

On October 19, 1987, the S&P 500 lost 20.5% in a single session. With the volatility of the time, under a Gaussian assumption, that was an event of more than twenty standard deviations: something that, if returns were truly normal, shouldn’t happen even once in the life of the universe, multiplied by billions. It happened, and it is the memento mori hanging on the wall of every volatility seller — the day that created the skew (see the Options page), rewrote the models and defined, once and for all, the trade described in these pages. This page is devoted to tails: what they really look like, when and how they arrive, what makes them (partially) manageable and what doesn’t. It is the least pleasant page on the site and the most important.

Ergodicity

Mon, 01 Jan 0001 00:00:00 +0000

Ergodicity#

This is both the most abstract page on the site and the one on which every concrete number depends. The question it answers sounds like a riddle: how can a bet with positive expectancy ruin almost everyone who plays it? The answer lies in a word borrowed from statistical physics — ergodicity — and in the distinction, simple and vertiginous, between the average computed across scenarios and the average computed across time.